(self)
| 208 | return dataloader |
| 209 | |
| 210 | def train_dataloader(self) -> DataLoader: |
| 211 | dataloader = self.get_dataloader("train", batch_size=self.hparams.train_batch_size, shuffle=True) |
| 212 | t_total = ( |
| 213 | (len(dataloader.dataset) // (self.hparams.train_batch_size * max(1, self.hparams.gpus))) |
| 214 | // self.hparams.gradient_accumulation_steps |
| 215 | * float(self.hparams.num_train_epochs) |
| 216 | ) |
| 217 | scheduler = get_linear_schedule_with_warmup( |
| 218 | self.opt, num_warmup_steps=self.hparams.warmup_steps, num_training_steps=t_total |
| 219 | ) |
| 220 | if max(scheduler.get_last_lr()) > 0: |
| 221 | warnings.warn("All learning rates are 0") |
| 222 | self.lr_scheduler = scheduler |
| 223 | return dataloader |
| 224 | |
| 225 | def val_dataloader(self) -> DataLoader: |
| 226 | return self.get_dataloader("val", batch_size=self.hparams.eval_batch_size) |
nothing calls this directly
no test coverage detected